Application of sequential factorial design and orthogonal array composite design (OACD) to study combination of 5 prostate cancer drugs |
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| Institution: | 1. Department of Urology, Ningbo First Hospital, Ningbo Hospital of Zhejiang University, Ningbo, Zhejiang 315010, China;2. School of Biomedical Engineering, Institute for Personalized Medicine, Shanghai Jiao Tong University, Shanghai 200030, China;1. Department of Mechanical Engineering, University of California, Riverside, Riverside, CA, United States;2. Department of Bioengineering, University of California, Riverside, Riverside, CA, United States;3. Materials Science and Engineering Program, University of California Riverside, Riverside, CA, United States;1. The N.1 Institute for Health (N.1), National University of Singapore, Singapore;2. Cancer Science Institute of Singapore, National University of Singapore, Singapore;3. Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore;1. School of Industrial Engineering and Center of Excellence for Intelligent-Based Experimental Mechanic, College of Engineering, University of Tehran, Tehran, Iran;2. Department of Industrial Engineering, University of Tafresh, Iran;3. Institute for Digital Ecosystems & Business Intelligence, Curtin University of Technology, Perth, Australia;1. Department of Mathematics, Faculty of Science, Zagazig University, Zagazig 44519, Egypt;2. Faculty of Mathematics and Statistics, Central China Normal University, Wuhan 430079, China;1. Siberian Federal University, Svobodni av., 79, 660041 Krasnoyarsk, Russia;2. Siberian State Technological University, Mira av., 82, 660049 Krasnoyarsk, Russia;1. Department of Mechanical Engineering, SV college of engineering, Tirupati, Andhra Pradesh, India - 517503;2. Department of Mechanical Engineering, M.I.T.S, Madanapalle, Andhra Pradesh, India -517325 |
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| Abstract: | Prostate cancer is one of the most common cancers among men in the United States. It is also a major leading cause of cancer death among men of all races. In order to treat prostate cancer, drug combinations are often applied. Drug combinations target at different pathways of cells can potentially lead to higher efficacy and lower toxicity due to drug synergy. In this paper, we sequentially applied a two-level design and a follow-up orthogonal array composite design (OACD) to investigate combinations of five anti-cancer drugs, namely, doxorubicin, docetaxel, paclitaxel, cis-dichlorodiamine platinum and dihydroartemisinin. Our initial screening using a two-level full factorial design identified doxorubicin and docetaxel as the most significant drugs. A follow-up experiment with an OACD revealed more complicated drug interactions among these 5 anti-cancer drugs. Quadratic effects of doxorubicin and paclitaxel appeared to be significant. A further investigation on contour plots of all the two-drug pairs indicated that combination of doxorubicin and docetaxel are the most effective companion, while the combination of cis-dichlorodiamine platinum and dihydroartemisinin showed unknown antagonistic effects which diminished the individual drug anti-cancer efficacy. These observations have significant practical implications in the understanding of anti-cancer drug mechanism that can facilitate clinical practice of better drug combinations. |
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| Keywords: | Anticancer Drug combination Factorial design Stepwise regression Orthogonal array composite design |
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